In recent years, federated learning was applied successfully in many different tasks. In [1]}, [2]}, federated learning is used in wake-word detection for a digital assistant. Federated learning was also applied in speech emotion detection [3]}. In [4]}, federated learning is used for mobile keyboard prediction. Another example is in the medical area, where more and more data is available from hospitals, clinics, or patients, but strict privacy requirements limit its use. In this situation, federated learning promises a compromise that maintains privacy while allowing to improve the quality of healthcare through big-data-driven AI [5]}.
